[pocketarc]

In the olden days, I enjoyed Opus 3 because it was easy to have it sound way more human than GPT.

Nowadays, with the focus on agentic use and coding, it seems models have all been RLHF’d to death, it’s so incredibly hard to have them write in a different voice than their default. I put together a skill to review its writing and have it edit its own output (e.g. code comments), which does make a difference, but isn’t perfect.

What, if anything, do people do for writing? That feels like a neglected side of LLMs. They’ll make 100 Bash calls referencing ancient commands without batting an eye but heaven forbid they use something other than “load-bearing” while talking. For something trained on “all the human knowledge” it’s incredible how limited their default vocabulary seems to be.

[Retr0id]

> What, if anything, do people do for writing?

I use a keyboard, personally.

[bunderbunder]

Amen.

At work our documentation isn’t just getting littered with annoying jargon. It isn’t just all the hallucinations, either. (Since when has documentation ever been 100% trustworthy?) It’s that it’s so poorly written and structured that it’s becoming borderline incomprehensible.

My company is currently considering making, “Why should I bother to read something you didn’t bother to write?” an official policy because even the executives are starting to burn out on all the time they have to spend wading through slop.

[mywittyname]

I wish my company would do this. A coworker pulled an all nighter before a vacation and just left me with a million line claude summary of their work then just fucked off. The message was two-part due to size and lacked basic stuff like, "how to run".

He's going to be annoyed that none of that work was used. But the reality is, at least 75% of claude generated text is pointless.

[xyzzy_plugh]

Somewhat off topic but every time I've experienced this sort of thing it was management's fault. If an engineer needs to pull an all nighter and hand off a pile of garbage then someone in management fucked up. If they can't see this scenario happening a mile away then they aren't paying attention.

It's easy to blame the engineer, but all too often they don't deserve it.

Sorry that happened to you.

[chrisandchris]

If it wasn't worth your time writing, it isn't worth my time reading.

[madcaptenor]

ai;dr

[BurningFrog]

Haven't done it, but letting an AI polish a manual first draft might be the best of both worlds?

[wren6991]

It tends not to improve things. Besides the generally bland and muddied style, and the low-fidelity reinterpretation of your points, they also have a habit of randomly deleting sentences that didn't spark joy for them but were actually important.

I've found them useful to review docs for factual consistency and potential sources of confusion, but the correct workflow from that point is IMO to correct the draft yourself and then say "better now?"

[recursivecaveat]

When the LLM decides to drive-by rephrase me when making a functional change it drives me up the wall haha.

Woah woah woah human, you can't just say there are "far too many" pipes with similar names to abbreviate their labels, the most I'll allow you is a "large number".

[Retr0id]

The "polish" is the worst part!

[pegasus]

This, a thousand times. As the ratio of code to human writing necessarily [1] goes up, they become not just smarter, but more precise and technical, which requires them to use more jargon. You could say they become more nerdy. Hence, text generated by these models will become more easily recognizable, at least by default, when not asking them to twist themselves into something else via prompting — which degrades intelligence. This is a good thing, in my book, given all the slop we already have to contend with.

Of course there will be models trained on much less code and technical writing, and they will create more natural sounding prose, but they will lack the deep intelligence of frontier models. Seems like a fair tradeoff.

[1] watch the first couple of minutes on this bycloud video on scaling training data mixtures: https://www.youtube.com/watch?v=aD93kfArOik

[postalcoder]

It's why I like Gemini 3.1 Pro. That it sounds much more human than other LLMs is testament to Google's inability to post train.

gemini-2.5-pro-experimental was the GOAT, though. It was an emotional wreck, down in the dumps and feeling terrible for itself after failing to patch a file several times. Very amusing to read, all the while watching it make a mess of my codebase.

[boofus]

Good. I don't want LLMs sounding human. I want the ability to shame and discredit anyone passing the job of prose to a machine. There's an art to writing, and hopefully LLMs never truly get it right.

[constantius]

Agreed. The only goal of these skills/tricks/requests for humanising LLM writing is to be able to pass it off as your own, because they know it's shameful and want to avoid the opprobrium.

Some will say it's just for their own quality of life when they're reading LLM output, or "just for docs", but this is an extremely marginal use case.

[queenkjuul]

I don't want LLM docs either

[antonvs]

> I want the ability to shame and discredit anyone passing the job of prose to a machine.

What about people who don’t speak your language well?

[zahlman]

I've dealt with many people by now who would copy and paste from an LLM for that exact reason, typically entirely unaware of how obvious it was that the result came from an LLM with no style guidance, and of course completely lacking any ability to verify that their intent was faithfully conveyed.

I would rather learn their language than continue interacting like that.

[antonvs]

I deal with people in five other countries in a daily basis, and LLMs have only been a benefit in terms of improving communication.

You claim you’d “rather learn their language”, but it’s an empty claim. How many languages have you learned for this reason?

[mhitza]

> Nowadays, with the focus on agentic use and coding, it seems models have all been RLHF’d to death

This has also lead to unrelated associations by which some people went from seeing better coding capabilities and extrapolate to assuming better thinking overall. One only has to watch youtube videos of AI "normies" trying to use LLMs the intended way to see that the improvements on coding doesn't translate to other applications. Basically from AGI "goals" they are now hyperfocused on coding agents, until the next marketing breakthrough rears its head.

[sheepscreek]

Agreed. I think we’re entering an era where some level of specialization for general LLMs is a good thing. Particularly between tuning for agentic use cases (where you want agency with a ton of guardrails and control) and writing which is more creative - you want the model to take the occasional risk and not sound like a monotonic robot. Having trained models first-hand, I can see the distinct use-cases clearly that are odds with one another.

[Wowfunhappy]

For what it's worth, Anthropic seems to be keeping Opus 3 available on claude.ai, perhaps for this reason, so you're free to use it if you want to.

[p-e-w]

> Nowadays, with the focus on agentic use and coding, it seems models have all been RLHF’d to death

I don’t get it. If nobody likes this writing style, how can it be the result of human feedback? Something else is going on.

[pathsjs]

It's not that the writing style is bad; in fact LLMs write actually pretty well. It's just too much overfitted. And even a style that, in itself, is pleasurable to read, becomes annoying when the same figures of speech are used over and over again.

[anon373839]

Because LLMs are pattern-extenders that have nothing to say. The training overfitted to the grace notes in good writing. And since LLMs can’t wield language with purpose or experience the feeling of the words, they use these devices arbitrarily.

I think this is the same flaw as coding agents seeing in every problem the call for a “smoke test” or the use of some unnecessary design pattern. The truest part of AI is the A.

[Wowfunhappy]

Because humans do like it, in reasonable quantities. The AI overlearns this and does it too much.

[yusefnapora]

It's not that nobody likes it, in fact the problem is that people like each instance of it well enough in isolation. Millions of people think it's "good enough," so it gets amplified and repeated until every PR description starts to sound like a toothpaste jingle.

[zahlman]

Because you can't actually do "good writing" by repeatedly applying the supposed idioms thereof. The tiny subsegment of humanity responsible for the RLHF don't necessarily have any good taste for writing; but even if they did, it's orders of magnitude harder to communicate than to make judgments of short samples, and communicating it by making those judgments is surely impossible.

Edit: I see that you got multiple replies all basically saying the same thing in very different words. There's an exquisite irony to that, I think.

[Bawoosette]

For "agentic use and coding," they are trained to take useful actions, not produce desirable natural language writing.

[itopaloglu83]

Maybe it’s the dead internet.

All the bots and other LLMs providing feedback, so in reality it’s reflecting the reality in a sense.

[jappgar]

every one-hit wonder asks the same question.

we liked it until we didn't.

[michelb]

i hate it, but plenty of people DO like it and plenty of people talk and write like that. It’s just corpspeak, being used a lot in the valley and beyond. And all upcoming hustlers running startups now feel the need to speak like that, feeding this machine.